학술논문
ConFusion: Sensor Fusion for Complex Robotic Systems Using Nonlinear Optimization
Document Type
Periodical
Author
Source
IEEE Robotics and Automation Letters IEEE Robot. Autom. Lett. Robotics and Automation Letters, IEEE. 4(2):1093-1100 Apr, 2019
Subject
Language
ISSN
2377-3766
2377-3774
2377-3774
Abstract
We present ConFusion, an open-source package for online sensor fusion for robotic applications. ConFusion is a modular framework for fusing measurements from many heterogeneous sensors within a moving horizon estimator. ConFusion offers greater flexibility in sensor fusion problem design than filtering-based systems and the ability to scale the online estimate quality with the available computing power. We demonstrate its performance in comparison to an iterated extended Kalman filter in visual-inertial tracking, and show its versatility through whole-body sensor fusion on a mobile manipulator.